# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Tests for MapDefunOp."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

from tensorflow.contrib.data.python.ops import map_defun
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import function
from tensorflow.python.framework import ops
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import check_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test


class MapDefunTest(test.TestCase):

  def testMapDefun_Simple(self):

    @function.Defun(dtypes.int32)
    def simple_fn(x):
      return x * 2 + 3

    with self.test_session():
      nums = [[1, 2], [3, 4], [5, 6]]
      elems = constant_op.constant(nums, dtype=dtypes.int32, name="data")
      r = map_defun.map_defun(simple_fn, [elems], [dtypes.int32], [(2,)])[0]
      expected = elems * 2 + 3
      self.assertAllEqual(self.evaluate(r), self.evaluate(expected))

  def testMapDefun_MismatchedTypes(self):

    @function.Defun(dtypes.int32)
    def fn(x):
      return math_ops.cast(x, dtypes.float64)

    with self.test_session():
      nums = [1, 2, 3, 4, 5, 6]
      elems = constant_op.constant(nums, dtype=dtypes.int32, name="data")
      r = map_defun.map_defun(fn, [elems], [dtypes.int32], [()])[0]
      with self.assertRaises(errors.InvalidArgumentError):
        self.evaluate(r)

  def testMapDefun_MultipleOutputs(self):

    @function.Defun(dtypes.int32)
    def fn(x):
      return (x, math_ops.cast(x * 2 + 3, dtypes.float64))

    with self.test_session():
      nums = [[1, 2], [3, 4], [5, 6]]
      elems = constant_op.constant(nums, dtype=dtypes.int32, name="data")
      r = map_defun.map_defun(fn, [elems], [dtypes.int32, dtypes.float64],
                              [(2,), (2,)])
      expected = [elems, elems * 2 + 3]
      self.assertAllEqual(self.evaluate(r), self.evaluate(expected))

  def testMapDefun_ShapeInference(self):

    @function.Defun(dtypes.int32)
    def fn(x):
      return x

    nums = [[1, 2], [3, 4], [5, 6]]
    elems = constant_op.constant(nums, dtype=dtypes.int32, name="data")
    result = map_defun.map_defun(fn, [elems], [dtypes.int32], [(2,)])[0]
    self.assertEqual(result.get_shape(), (3, 2))

  def testMapDefun_PartialShapeInference(self):

    @function.Defun(dtypes.int32)
    def fn(x):
      return x

    elems = array_ops.placeholder(dtypes.int64, (None, 2))
    result = map_defun.map_defun(fn, [elems], [dtypes.int32], [(2,)])
    self.assertEqual(result[0].get_shape().as_list(), [None, 2])

  def testMapDefun_RaisesErrorOnRuntimeShapeMismatch(self):

    @function.Defun(dtypes.int32, dtypes.int32)
    def fn(x, y):
      return x, y

    elems1 = array_ops.placeholder(dtypes.int32)
    elems2 = array_ops.placeholder(dtypes.int32)
    result = map_defun.map_defun(fn, [elems1, elems2],
                                 [dtypes.int32, dtypes.int32], [(), ()])
    with self.test_session() as sess:
      with self.assertRaisesWithPredicateMatch(
          errors.InvalidArgumentError,
          "All inputs must have the same dimension 0."):
        sess.run(result, feed_dict={elems1: [1, 2, 3, 4, 5], elems2: [1, 2, 3]})

  def testMapDefun_RaisesDefunError(self):

    @function.Defun(dtypes.int32)
    def fn(x):
      with ops.control_dependencies([check_ops.assert_equal(x, 0)]):
        return array_ops.identity(x)

    elems = constant_op.constant([0, 0, 0, 37, 0])
    result = map_defun.map_defun(fn, [elems], [dtypes.int32], [()])
    with self.test_session():
      with self.assertRaises(errors.InvalidArgumentError):
        self.evaluate(result)


if __name__ == "__main__":
  test.main()
